Ulcerative colitis (UC) is a chronic inflammatory disease of the colon. Patients with extensive UC of more than 8 years duration have an increased risk of colorectal cancer (CRC) which approximates 0.5-1% per year of colitis; this leads to a recommendation for life-long surveillance colonoscopy. However, cancer surveillance for these patients is expensive, time-consuming and invasive. Moreover, the sensitivity of detecting dysplasia in colonoscopy is only moderate, largely due to the difficulty in detecting flat dysplastic lesions in the setting of UC. An objective molecular biomarker for dysplasia would have great clinical value in the management of cancer risk in UC patients. In our efforts for biomarker development for UC dysplasia, we previously discovered that the non-dysplastic mucosa is genetically abnormal in UC patients who have neoplasia elsewhere in their colon (progressors), i.e. there is a field defect phenomenon in UC progressors which is not present in UC non- progressors (patients without dysplasia). Recently, we further discovered that the same field defect extends to abnormal expression of proteins in the non-dysplastic mucosa from the rectum of UC progressors. These findings are exciting because these protein changes occur in randomly sampled colon and/or rectal mucosa regardless of whether dysplasia is present or not. These abnormally expressed proteins could be valuable for developing biomarkers that are effective and relatively non-invasive for detecting UC dysplasia. One can envision that a random biopsy from an unprepped rectum would suffice to provide the sample needed for biomarker testing. This proposal seeks to develop molecular biomarkers for two purposes: 1) to detect current dysplasia/cancer; 2) to predict (track) future dysplasia/cancer progression. Molecular biomarkers will be developed by using cutting edge quantitative and then evaluated and validated using immunohistochemistry (IHC) and targeted proteomics methods. Finally, the molecular biomarkers will be evaluated for their clinical value in detecting and predicting UC neoplasia progression in different cohorts. We believe that this project will greatly improve the current surveillance strategy for early detection of UC-associated colorectal cancer.